If the models already work, why would it even require a cloud component? That's just risky, complex, and costly. Let the device do its thing, doc writes down the findings, data gets deleted, and device ready for next patient.
They aren't using AI or the cloud component to do what they can already do.
The whole promise that all these companies are pitching is to aggregate patient data over time, tie it to clinically measurable metrics so they can detect, prevent or treat things better. In your example the idea would be the model in the cloud is aggregating all the patient health record data, tying that to the xrays of those same patients, so that in the future the model can see things in x-rays that indicate disease or are predacessors to disease before we humans can even spot them.
All that takes money.
If the vendor wants to improve the model, they can ask for anonymized data from physicians, if they're willing to provide it. That's their cost of developing a better product, just like anyone in any industry pays a price in some way to improve their product.
This stuff can't run locally, it's cloud connected by design. It's cloud connected by design because the company's value pitch is on the data, not the hardware. They loose money or break even on the capital hardware. This is always the case, intuitive makes their money on the instruments, others make it on the subscription fee.
If you want it this way, you'll end up paying a lot more for thr capital equipment.
There is no free lunch.